Transport Network Design Problem under Uncertainty: A Review and New Developments
operations - capacity, operations - performance, operations - reliability, planning - network design
network design problem (NDP), capacity, demand uncertainty
This paper aims to provide a state-of-the-art review of the transport network design problem (NDP) under uncertainty and to present some new developments on a bi-objective-reliable NDP (BORNDP) model that explicitly optimizes the capacity reliability and travel time reliability under demand uncertainty. Both are useful performance measures that can describe the supply-side reliability and demand-side reliability of a road network. A simulation-based multi-objective genetic algorithm solution procedure, which consists of a traffic assignment algorithm, a genetic algorithm, a Pareto filter, and a Monte-Carlo simulation, is developed to solve the proposed BORNDP model. A numerical example based on the capacity enhancement problem is presented to demonstrate the tradeoff between capacity reliability and travel time reliability in the NDP.
Permission to publish the abstract has been given by Taylor & Francis, copyright remains with them.
Chen, A., Zhou, Z., Chootinan, P., Ryu, S., Yang, C., & Wong, S.C. (2011). Transport Network Design Problem under Uncertainty: A Review and New Developments. Transport Reviews, Vol. 31, (6), pp. 743-768.